1. Field of the Invention
The present invention relates generally to using music detection to enhance speech communications. More particularly, the present invention relates to using music detection to enhance echo cancellation and speech coding.
2. Background Art
Conventional speech coding systems often employ voice activity detectors (“VADs”) to examine speech signals and differentiate between voice and background noise. However, conventional VADs often cannot differentiate music from background noise. As is known in the art, background noise signals are typically fairly stable as compared to voice signals. The frequency spectrum of voice signals (or unvoiced signals) changes rapidly. In contrast to voice signals, background noise signals exhibit the same or similar frequency for a relatively long period of time, and therefore exhibit heightened stability. Therefore, in conventional approaches, differentiating between voice signals and background noise signals is fairly simple and is based on signal stability. Unfortunately, music signals are also typically relatively stable for a number of frames (e.g. several hundred frames). For this reason, conventional VADs often fail to differentiate between background noise signals and music signals, and exhibit rapidly fluctuating outputs for music signals.
If a conventional VAD determines that its input signal does not represent a voice signal, it will often simply classify its input signal as background noise and the signal will be encoded accordingly. However, the input signal may in fact comprise music and not background noise, and encoding a music signal as background noise will result in a low perceptual quality, or in this case, poor quality music. Further, classifying the signal as background noise would also cause conventional echo cancellers to eliminate a music signal by attenuating the signal below the noise floor and replacing the music signal by comfort noise if the comfort noise option is enabled, or with silence if the comfort noise option is disabled.
Thus, there is need in the art for methods and systems that can efficiently classify signals as music signals, and utilize such classification to improve the perceptual quality of such signals.